Data Science environment sandbox based on Azure ML: 2-Week Implementation

Introducing our offering for organizations looking to build an efficient and standardized data science environment that supports MLOps practices on the Azure ML platform. Our service provides a hassle-free experience for quick adoption of Azure ML, with tailored education and support to enable your Data Science team. Our standardized Azure ML environment comes with pre-built templates for MLOps pipelines, which have been tried and tested in complex productization projects. This ensures that your team has access to the best practices in the industry, enabling fast and effective ML solution productization and scalability. Our service is designed for organizations who are either starting or are in the process of evaluating or adopting Azure ML. The service is tailored to be lightweight and fast, and consists of several phases, including a workshop to confirm the requirements and environment design, environment installation, Data Science team enablement and support, and possible extensions or following phases such as environment customization, implementation of example projects, and support in ML development and operations.

We've got a ton of experience in the field, and we offer three basic service packages that can be customized to fit your organization's data science and AI needs. Our packages are designed to tackle whatever challenges your company is facing and help you grow(details below).

I. Sandbox (included in the offer, estimated price: 15,000$): 

1. Setup all prerequisites (configuration of subscriptions, providers and AAD enterprise application) 
2. Configuration Azure DevOps Repository: 
   • Terraform templates 
   • Lingaro's best practices AzureML project repository template 
3. Azure Resource Manager setup 
4. Azure DevOps infrastructure deployment pipeline 
5. ADO CI/CD pipelines setup (integration with AzureML) 
6. Fully automated setup verifications 

II. Extended security (not included in the offer, possible extension): 

1. DEV, (QA optional), PROD environment deployment 
2. Configuration security layer (implementing security best practices for enterprise-ready solutions, critical from business perspective). 
3. Configuration environment disaster recovery & HA(high availability) 

III. Enterprise-ready(not included in the offer, possible extension): 

1. Advanced MLOps setup production-ready pipelines templates (model management, tracking) 
2. Advanced Data management production-ready pipelines templates (ETL, transformation) 
3. Advanced CI/CD for rapid development, code quality, unit testing, Azure ML integration testing and release pipeline 
4. Documentation and on-boarding for Lingaro MLOps framework 

We would be delighted to discuss the specific requirements of your organization and collaborate on tailoring a service package that best fits your needs. Please do not hesitate to contact us to schedule a consultation.